Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API

Desvignes, Thomas; Loher, Phillipe; Eilbeck, Karen; Ma, Jeffery; Urgese, Gianvito; Fromm, Bastian; Sydes, Jason; Aparicio-Puerta, Ernesto; Barrera, Victor; Espin, Roderic; Thibord, Florian; Bofill-De Ros, Xavier; Londin, Eric; Telonis, Aristeidis G.; Ficar

Publicación: BIOINFORMATICS
2020
VL / 36 - BP / 698 - EP / 703
abstract
Motivation: MicroRNAs (miRNAs) are small RNA molecules (similar to 22 nucleotide long) involved in post-transcriptional gene regulation. Advances in high-throughput sequencing technologies led to the discovery of isomiRs, which are miRNA sequence variants. While many miRNA-seq analysis tools exist, the diversity of output formats hinders accurate comparisons between tools and precludes data sharing and the development of common downstream analysis methods. Results: To overcome this situation, we present here a community-based project, miRNA Transcriptomic Open Project (miRTOP) working towards the optimization of miRNA analyses. The aim of miRTOP is to promote the development of downstream isomiR analysis tools that are compatible with existing detection and quantification tools. Based on the existing GFF3 format, we first created a new standard format, mirGFF3, for the output of miRNA/isomiR detection and quantification results from small RNA-seq data. Additionally, we developed a command line Python tool, mirtop, to create and manage the mirGFF3 format. Currently, mirtop can convert into mirGFF3 the outputs of commonly used pipelines, such as seqbuster, isomiR-SEA, sRNAbench, Prost! as well as BAM files. Some tools have also incorporated the mirGFF3 format directly into their code, such as, miRge2.0, IsoMIRmap and OptimiR. Its open architecture enables any tool or pipeline to output or convert results into mirGFF3. Collectively, this isomiR categorization system, along with the accompanying mirGFF3 and mirtop API, provide a comprehensive solution for the standardization of miRNA and isomiR annotation, enabling data sharing, reporting, comparative analyses and benchmarking, while promoting the development of common miRNA methods focusing on downstream steps of miRNA detection, annotation and quantification.

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Green published

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